Triple

T14609930
Position Surface form Disambiguated ID Type / Status
Subject Achtung, Europa! E342929 entity
Predicate creator P184 FINISHED
Object Peter Kohl E68442 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Peter Kohl | Statement: [Achtung, Europa!, creator, Peter Kohl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Kohl
Context triple: [Achtung, Europa!, creator, Peter Kohl]
  • A. Peter Kohl chosen
    Peter Kohl is a German businessman and author best known as the son of former German Chancellor Helmut Kohl.
  • B. Daniel Günther
    Daniel Günther is a German politician from the Christian Democratic Union (CDU) who serves as the Minister-President of the northern federal state of Schleswig-Holstein.
  • C. Georg Scholz
    Georg Scholz was a German painter associated with the New Objectivity movement, known for his socially critical, realist depictions of Weimar-era society.
  • D. Wolfgang Vogel
    Wolfgang Vogel was a prominent East German lawyer best known for brokering high-profile prisoner exchanges and political deals between East and West Germany during the Cold War.
  • E. Christian Scholz
    Christian Scholz is a German computer scientist and open-source developer known for his contributions to web technologies and social software.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44f0dd48190a78662b5998a6722 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda91d05e48190ac945e381d6d5dd9 completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:25 a.m.